The Intersection of Big Data Analytics and Digital Humanities: A Systematic Review of Definitions, Applications, and Challenges

This systematic literature review explores the intersection of big data analytics and digital humanities, focusing on definitions, applications, and challenges. By analyzing 37 relevant studies, the review found that big data in the humanities refers to the computational analysis of large volumes of digitized cultural data, while digital humanities integrates digital tools and methods into humanistic research. The literature reveals a wide range of applications, including text mining, network analysis, and machine learning, which enable new forms of inquiry and insight. However, challenges such as data complexity, methodological tensions, and skills gaps are also highlighted. The review concludes that big data methods have the potential to transform humanities research when used critically and in collaboration with humanistic expertise, requiring further research to develop robust methodologies and interdisciplinary collaborations.